Hi,
What would be the appropriate settings to run Spark with Kafka 10? My job
works fine with Spark with Kafka 8 and with Kafka 8 cluster. But its very
slow with Kafka 10 by using Kafka Direct' experimental APIs for Kafka 10 . I
see the following error sometimes . Please see the kafka parameters and the
consumer strategy for creating the stream below. Any suggestions on how to
run this with better performance would be of great help.
java.lang.AssertionError: assertion failed: Failed to get records for test
stream1 72 324027964 after polling for 120000
val kafkaParams = Map[String, Object](
"bootstrap.servers" -> kafkaBrokers,
"key.deserializer" -> classOf[StringDeserializer],
"value.deserializer" -> classOf[StringDeserializer],
"auto.offset.reset" -> "latest",
"heartbeat.interval.ms" -> Integer.valueOf(20000),
"session.timeout.ms" -> Integer.valueOf(60000),
"request.timeout.ms" -> Integer.valueOf(90000),
"enable.auto.commit" -> (false: java.lang.Boolean),
"spark.streaming.kafka.consumer.cache.enabled" -> "false",
"group.id" -> "test1"
)
val hubbleStream = KafkaUtils.createDirectStream[String, String](
ssc,
LocationStrategies.PreferConsistent,
ConsumerStrategies.Subscribe[String, String](topicsSet, kafkaParams)
)
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